• Journal of Korean Society of Transportation
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• v.24 no.6 s.92
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• pp.33-43
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• 2006

This research is to the selection of optimal probability distribution as well as the estimation for design hourly factor in consideration of traffic characteristic, such as road function, lane number and AADT. To accomplish the objectives, we are applied to various probability distribution using traffic data that observed at permanent traffic count points in 2005. The parameters or the selected 14 probability distribution were estimated based on the method of maximum likelihood and the validity condition of the estimated parameter The goodness-of-fit test, such as chi-square test. was performed as well as the estimation of design hourly factor. As a result, An appropriate distributions of each case were selected : Pearson V for two lane of rural roads, LogLogistic for the four lane of rural roads, LogLogistic for the urban roads, Extreme value for recreation roads. And optimal K factor are as following : $0.1{\sim}0.2 $ for two lane of rural roads, $0.09{\sim}0.14$ for the four lane of rural roads. $0.07{\sim}0.13$ for the urban roads, $0.1{\sim}0.2$ for recreation roads.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.1009-1019
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• 2009

In this research, various characteristics of South Korea's design flood have been examined by deriving appropriate design flood, using data obtained from careful observation of actual floods occurring in selected main watersheds of the nation. 19 watersheds were selected for research in Korea. The various characteristics of annual rainfall were analyzed by using a moving average method. The frequency analysis was decided to be performed on the annual maximum flood of succeeding one year as a reference year. For the 19 watersheds, tests of basic statistics, independent, homogeneity, and outlier were calculated per period of annual maximum flood series. By performing a test using the LH-moment ratio diagram and the Kolmogorov-Smirnov (K-S) test, among applied distributions of Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) distribution was found to be adequate compared with other probability distributions. Parameters of GEV distribution were estimated by L, L1, L2, L3 and L4-moment method based on the change in the order of probability weighted moments. Design floods per watershed and the periods of annual maximum flood series were derived by GEV distribution. According to the result of the analysis performed by using variation rate used in this research, it has been concluded that the time for changing the design conditions to ensure the proper hydraulic structure that considers recent climate changes of the nation brought about by global warming should be around the year 2002.

• Structural Engineering and Mechanics
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• v.70 no.4
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• pp.479-497
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• 2019

In the current code design, the use of a uniform internal pressure coefficient of cooling towers as internal suction cannot reflect the 3D characteristics of flow field inside the tower body with different ventilation rate of shutters. Moreover, extreme weather such as heavy rain also has a direct impact on aerodynamic force on the internal surface and changes the turbulence effect of pulsating wind. In this study, the world's tallest cooling tower under construction, which stands 210m, is taken as the research object. The algorithm for two-way coupling between wind and rain is adopted. Simulation of wind field and raindrops is performed iteratively using continuous phase and discrete phase models, respectively, under the general principles of computational fluid dynamics (CFD). Firstly, the rule of influence of 9 combinations of wind speed and rainfall intensity on the volume of wind-driven rain, additional action force of raindrops and equivalent internal pressure coefficient of the tower body is analyzed. The combination of wind velocity and rainfall intensity that is most unfavorable to the cooling tower in terms of distribution of internal pressure coefficient is identified. On this basis, the wind/rain loads, distribution of aerodynamic force and working mechanism of internal pressures of the cooling tower under the most unfavorable working condition are compared between the four ventilation rates of shutters (0%, 15%, 30% and 100%). The results show that the amount of raindrops captured by the internal surface of the tower decreases as the wind velocity increases, and increases along with the rainfall intensity and ventilation rate of the shutters. The maximum value of rain-induced pressure coefficient is 0.013. The research findings lay the basis for determining the precise values of internal surface loads of cooling tower under extreme weather conditions.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.81-96
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• 2017

Along with climate change, it is reported that the scale and the frequency of extreme climate events (e.g. heavy rain, typhoon, etc.) show unstable tendency of increase. In case of Korea, also, the frequency of heavy rainfall shows increasing tendency, thus causing natural disaster damage in downtown and agricultural areas by rainfall that exceeds the design criteria of hydraulic structures. In order to minimize natural disaster damage, it is necessary to analyze how extreme precipitation event changes under climate change. Therefore a new design criteria based on non-stationarity frequency analysis is needed to consider a tendency of future extreme precipitation event and to prepare countermeasures to climate change. And a quantitative and objective characteristic analysis could be a key to preparing countermeasures to climate change impact. In this study, non-stationarity frequency analysis was performed and inundation risk indices developed by 4 inundation characteristics (e.g. inundation area, inundation depth, inundation duration, and inundation radius) were assessed. The study results showed that future probable rainfall could exceed the existing design criteria of hydraulic structures (rivers of state: 100yr-200yr, river banks: 50yr-100yr) reaching over 500yr frequency probable rainfall of the past. Inundation characteristics showed higher value in the future compared to the past, especially in sections with tributary stream inflow. Also, the inundation risk indices were estimated as 0.14 for the past period of 1973-2015, and 0.25, 0.29, 1.27 for the future period of 2016-2040, 2041-2070, 2071-2100, respectively. The study findings are expected to be used as a basis to analyze future inundation damage and to establish management solutions for rivers with inundation risks.

• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.165-191
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• 2006

I examine the relationship between values and security designs of MBS(mortgage-backed securities), using four different types of them. To this end I consider a pass-through and three different kinds of CMOs(collateralized mortgage obligations). It turns out that the pass-through has the lowest value and that, among CMOs, that of a senior-mezzanine-subordinate design has the highest value. This implies that CMOs of a simple and extreme design, like that of a senior-subordinate design, are not likely to be the best CMOs for risk averse buyers. Another critical finding is that the optimal security design of CMOs or MBS does exist in the form of an interior solution. This indicates that MBS issuers could charge higher prices of MBS given their underlying mortgages by tailoring MBS security designs to the needs or utilities of MBS buyers, usually by removing and combining risks of component tranches of MBS. Accordingly a thorough study of realistic utility functions of MBA buyers could enhance the values or prices of MBS to be issued.

• Korean Management Science Review
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• v.31 no.2
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• pp.33-48
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• 2014

It is important to maintain on operational availability of aircraft during wartime. The KF-16 fighter, the backbone of the ROKAF (Republic Of Korea Air Force), has a single engine. Therefore, the engine has a critical influence on operational availability. The purpose of this study is to estimate optimal levels of spare part inventories concerning both engines and modules. That is provided by linear programming methods utilizing a developed meta-model. For drawing out the meta-model, we develop a simulation model which can consider wartime demands. In the previous study, $2^k$ factorial design method is used to check the influence of each independent variable. That method requires relatively many scenarios because every extreme value combination of independent variables should be checked. However, this study adopts NOLH (Nearly Orthogonal Latin Hypercube) as an experimental design. By adopting NOLH, this study increases not only efficiency but also accuracy. That is proven by comparing the validity of the developed meta-model on both experimental designs. This study also utilizes the OptQuest simulation tool in ARENA to derive the optimal level of spare stocks. By comparing the result of OptQuest to that of the developed meta-model, the validity of this study is secured.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.3
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• pp.53-62
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• 2009

This study was carried out to select optimal probability distribution based on design accumulated monthly mean inflow from the viewpoint of drought by Gamma (GAM), Generalized extreme value (GEV), Generalized logistic (GLO), Generalized normal (GNO), Generalized pareto (GPA), Gumbel (GUM), Normal (NOR), Pearson type 3 (PT3), Wakeby (WAK) and Kappa (KAP) distributions for the observed accumulative monthly mean inflow of Chungjudam. L-moment ratio was calculated using observed accumulative monthly mean inflow. Parameters of 10 probability distributions were estimated by the method of L-moments with the observed accumulated monthly mean inflow. Design accumulated monthly mean inflows obtained by the method of L-moments using different methods for plotting positions formulas in the 10 probability distributions were compared by relative mean error (RME) and relative absolute error (RAE) respectively. It has shown that the design accumulative monthly mean inflow derived by the method of L-moments using Weibull plotting position formula in WAK and KAP distributions were much closer to those of the observed accumulative monthly mean inflow in comparison with those obtained by the method of L-moment with the different formulas for plotting positions in other distributions from the viewpoint of RME and RAE.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.252-263
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• 2008

This study was conducted to derive the optimal regionalization of the precipitation data which can be classified on the basis of climatologically and geographically homogeneous regions all over the regions except Cheju and Ulreung islands in Korea. A total of 65 rain gauges were used to regional analysis of precipitation. Annual maximum series for the consecutive durations of 1, 3, 6, 12, 24, 36, 48 and 72hr were used for various statistical analyses. K-means clustering mettled is used to identify homogeneous regions all over the regions. Five homogeneous regions for the precipitation were classified by the K-means clustering. Using the L-moment ratios and Kolmogorov-Smirnov test, the underlying regional probability distribution was identified to be the generalized extreme value (GEV) distribution among applied distributions. The regional and at-site parameters of the generalized extreme value distribution were estimated by the linear combination of the probability weighted moments, L-moment. The regional and at-site analysis for the design rainfall were tested by Monte Carlo simulation. Relative root-mean-square error (RRMSE), relative bias (RBIAS) and relative reduction (RR) in RRMSE were computed and compared with those resulting from at-site Monte Carlo simulation. All show that the regional analysis procedure can substantially reduce the RRMSE, RBIAS and RR in RRMSE in the prediction of design rainfall. Consequently, optimal design rainfalls following the regions and consecutive durations were derived by the regional frequency analysis.

• Science of Emotion and Sensibility
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• v.13 no.4
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• pp.669-676
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• 2010

Regulatory fit occurs when the way people act accords with their goal orientation the activity. When there is regulatory fit, to pursue a goal feels light and also increases the value of what a person is doing-value from fit. Value from fit can be transferred to other value experiences such as monetary value. Present research proposes that regulatory fit occurs when the domain in which a decision or an evaluation is made sustains the decision maker's chronic goal orientation, and this regulatory fit affects the value that he or she assigns to the object. In Experiment 1, participants with chronic promotion or prevention focus evaluated their preference and purchase intention on 14 design products including positive and negative emotional valences. Results showed that evaluations on the product design (promotion domain) were more extreme under promotion than prevention, F(1, 95) 4.87, p < .05. In Experiment 2 with 16 moral scenarios including prescriptive and proscriptive morality, prevention-focus individuals evaluated immoral behaviors as more immoral than promotion-focus individuals only in the proscriptive scenarios (prevention domain), F(1, 139) = 4.14, p < .05. In prescriptive scenarios, regulatory fit effect was not found. Findings from both experiments suggest that regulatory fit occurs when the domain of an issue that people engage in sustains their goal orientation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.165-174
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• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.